Lead Data Scientist, GFT

Job Description

Job Description What is the opportunity? Are you a hands-on AI innovator who loves solving complex problems, mentoring rising stars, and building cutting-edge ML and GenAI solutions? RBC is looking for a Lead Data Scientist to help shape the future of our AI capabilities by creating impactful machine learning and generative AI solutions using technologies such as LLMs, RAG systems, transformers, and modern ML frameworks while scaling our AI engineering culture. You'll spend at least 60% of your time developing, training, and deploying ML and GenAI models that power critical risk management systems, while also inspiring a small team of junior data scientists and ML engineers to do their best work. Your contributions will elevate the risk management capabilities of the firm by unlocking data from various sources, such as the enterprise GRC platform, to improve insights and monitor KRIs. If you're excited about tackling complex risk challenges through AI, pushing the boundaries of what's possible with generative AI in risk management, and growing the next generation of data scientists, let's talk. What will you do? Lead by example by designing, implementing, and optimizing advanced statistical and machine learning models from ideation through production deployment, solving real-world risk management challenges with rigor and innovation. Push the adoption of next-generation AI by spearheading the development of LLM-powered solutions, RAG systems, and generative AI applications that transform risk identification, automate complex workflows, and unlock new business value. Mentor and develop emerging talent in the data science and ML engineering community, fostering a culture of curiosity, experimentation, and technical excellence. Translate data into decisions by collaborating with product, business, and technology teams to identify high-impact opportunities, refine hypotheses, test assumptions, and transform complex analytical findings into clear, actionable recommendations that drive strategic decisions. Champion modern ML practices like responsible AI frameworks, model governance, MLOps automation, A/B testing, and reproducible research workflows to keep RBC at the forefront of data science innovation. Design and deploy scalable solutions from architectural decisions to hands-on model development, ensuring solutions meet the highest standards of accuracy, performance, interpretability, safety and business impact. Collaborate across the organization to identify requirements, scope data science initiatives, and build strong partnerships with stakeholders across business lines and technology teams. Continuously explore emerging technologies and methodologies, staying ahead of the curve on LLM advancements, fine-tuning techniques, transfer learning, and other cutting-edge approaches to keep RBC competitive in AI. Drive innovation through experimentation, leveraging research rigor to test novel ML approaches, prototype proofs-of-concept, and validate bus